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基于响应面法的盾构施工膨润土改良参数优化

徐征杰, 郭晓阳

徐征杰, 郭晓阳. 基于响应面法的盾构施工膨润土改良参数优化[J]. 岩土工程学报, 2021, 43(1): 194-200. DOI: 10.11779/CJGE202101023
引用本文: 徐征杰, 郭晓阳. 基于响应面法的盾构施工膨润土改良参数优化[J]. 岩土工程学报, 2021, 43(1): 194-200. DOI: 10.11779/CJGE202101023
XU Zheng-jie, GUO Xiao-yang. Optimization of bentonite parameters for shield tunneling based on response surface method[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(1): 194-200. DOI: 10.11779/CJGE202101023
Citation: XU Zheng-jie, GUO Xiao-yang. Optimization of bentonite parameters for shield tunneling based on response surface method[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(1): 194-200. DOI: 10.11779/CJGE202101023

基于响应面法的盾构施工膨润土改良参数优化  English Version

详细信息
    作者简介:

    徐征杰(1982— ),男,硕士,高级工程师,主要从事地下工程施工方面的技术研究工作。E-mail: bepatient@163.com

    通讯作者:

    郭晓阳, E-mail: 651402719@qq.com

  • 中图分类号: TU411;U455

Optimization of bentonite parameters for shield tunneling based on response surface method

  • 摘要: 为确定福州地铁4号线金牛山—工业路盾构区间强风化花岗岩地层中的膨润土改良最优参数,分别选择膨润土泥浆浓度、掺入比和盾构推进速度3个影响因素,以渣土塌落度、渗透系数和改良成本为响应值。采用中心复合试验设计方法进行了20组试验,分别构建了各响应值的响应面函数。试验结果表明,膨润土泥浆浓度、掺入比和盾构推进速度对渣土改良效果均有较大影响,且各因素之间存在显著交互作用。利用响应面-满意度函数,将渣土改良的3个响应值优化问题转化为单一响应值优化,获得强风化花岗岩地层在不同盾构推进速度下的最优改良参数。该方法科学合理,为金牛山—工业路盾构区间在强风化花岗岩内的高效施工提供了技术保障。
    Abstract: In order to determine the optimal parameters of bentonite improvement in the strongly weathered granite strata in Jinniu Mountain-Gongye Road shield interval of Fuzhou metro line 4, the concentration and mixing ratio of bentonite slurry and advancing speed of shield are selected as the three factors, and the slump, permeability and improvement cost of soils are taken as the response values. The central composite design (CCD) method is used to carry out 20 groups of tests, and the response surface functions of each response value are constructed respectively. The results show the concentration and mixing ratio of bentonite slurry and advancing speed of shield all have great influences on the improvement effect of soils, and there is a significant interaction among these factors. By using the response surface-satisfaction function, the optimization problem of three response values for soil improvement is transformed into that of a single response value, and the optimal improvement parameters of the strongly weathered granite strata under different advancing speeds of shield tunneling are obtained. The proposed method is scientific and reasonable, which provides a technical guarantee for the efficient construction of Jinniu Mountain-Gongye Road shield interval in the strongly weathered granite strata.
  • 图  1   粒径级配曲线

    Figure  1.   Grain-size distribution curve

    图  2   土样制备

    Figure  2.   Preparation of soil samples

    图  3   盾构机土舱示意图

    Figure  3.   Schematic diagram of earth chamber of shield machine

    图  4   盾构机土舱相似模型

    Figure  4.   Similar model for EPB shield chamber

    图  5   改良效果对比

    Figure  5.   Comparison of improvement effect

    图  6   塌落度响应曲面图

    Figure  6.   Response surface of slump

    图  7   渗透系数响应曲面图

    Figure  7.   Response surface of permeability coefficient

    图  8   不同推进速度下满意度响应曲面图

    Figure  8.   Satisfaction response surface under different advancing speeds

    图  9   试验段改良情况

    Figure  9.   Improvement of test sections

    表  1   膨润土基本性质表

    Table  1   Basic properties of bentonite

    吸蓝量/(g·100g-1)胶质价/(mL·15g-1)膨胀倍数/(mL·g-1)pH值细度(200目)
    32400208.0~9.595
    下载: 导出CSV

    表  2   中心复合试验结果表

    Table  2   Results of central composite tests

    运行序浓度/%掺入比/%推进速度/(cm·min-1)塌落度/mmlgK40
    15153.535-4.83
    2882.58-5.11
    35151.5113-4.89
    411351.5140-5.64
    58252.5122-4.98
    611151.556-5.41
    75351.5231-4.68
    85353.5201-4.72
    98254.2153-4.60
    108252.5147-4.96
    113252.5183-4.57
    128252.5151-4.93
    138422.5191-5.17
    1413252.5106-5.42
    158252.5138-5.04
    1611153.530-5.14
    178250.8171-5.01
    188252.5147-5.00
    1911353.5155-5.39
    208252.5141-4.98
    下载: 导出CSV

    表  3   回归模型方差分析表

    Table  3   Analysis of variance of regression model

    预测响应值变异来源平方和均方FP备注
    Y1模型64180.169168.5952.78< 0.0001显著
    X17894.867894.8645.45< 0.0001
    X247051.4447051.44270.88< 0.0001
    X31629.431629.439.380.0098
    X1 X2709.08709.084.080.0662
    X1 X31178.791178.796.790.0230
    X2 X3965.22965.225.560.0362
    X224751.344751.3427.350.0002
    失拟项1516.83216.691.910.2472不显著
    Y2模型1.280.2127.00< 0.0001显著
    X11.061.06134.01< 0.0001 
    X20.010.011.120.3102 
    X30.020.022.080.1733 
    X1 X20.060.068.110.0137 
    X1 X30.030.034.130.0631 
    X220.100.1012.550.0036 
    失拟项0.100.017.760.0186不显著
    下载: 导出CSV

    表  4   响应优化目标范围

    Table  4   Target ranges of response optimization

    响应塌落度/cmlgK40膨润土单耗/(kg/环)
    优化目标100<Y1<200,Y1=150最为理想-5.45<Y2<-4.45320<Y3<1645
    下载: 导出CSV

    表  5   膨润土最优改良参数表

    Table  5   Optimal parameters of bentonite improvement

    推进速度/(cm·min-1)膨润土泥浆浓度/%膨润土泥浆掺入比/%整体满意度极大值
    1.57.823.70.718
    2.07.824.90.702
    2.57.625.50.678
    3.08.027.00.649
    3.57.827.60.610
    下载: 导出CSV
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  • 收稿日期:  2020-05-01
  • 网络出版日期:  2022-12-04
  • 刊出日期:  2020-12-31

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